Director, Capacity Planning and Resource Management

Renesas Electronics•San Jose, CA

6d•$216,000 - $270,000•Onsite

About The Position

We are looking for a transformational leader to build and lead Business & Operational Analytics for Power Computing Products (PCP), the fastest-growing business within the Power Products Group (PWR), with a charter to scale the capability across PWR. Today, we have strong visibility into financial outcomes—revenue, GM%, and OM%—but limited visibility into the operational drivers behind those outcomes. This role will establish the metrics, analytics, systems, and operating mechanisms needed to provide leadership with a fact-based view of NPI health, operational performance, productivity, risks, and business impact. This is not a reporting or dashboard role. The leader will define the future-state operating model, build the organization and analytics capability, leverage AI, and drive measurable business transformation.

Requirements

Bachelor’s degree in engineering, Computer Science, Data Science, Business, Operations, or related field; advanced degree preferred.
7–10+ years of progressive experience in business/operational analytics, engineering operations, NPI, transformation, strategy, or related fields.
Demonstrated experience building business performance-management or operational analytics capabilities.
Proven ability to translate complex data into actionable insights for senior executives.
Strong understanding of NPI/product development and operational execution.
Experience building teams, processes, and capabilities from the ground up.
Strong business acumen and ability to connect operational performance to financial outcomes.
Proven ability to influence cross-functional teams and drive change without direct authority.
Excellent executive communication and presentation skills.

Nice To Haves

Semiconductor, electronics, hardware, or high-tech industry experience.
NPI/product lifecycle management experience.
Experience across Engineering, Operations, Quality, Supply Chain, and Finance.
Experience with advanced analytics, predictive modeling, AI, or machine learning.
Experience scaling capabilities from a business unit to an enterprise.
Experience with modern data platforms, BI tools, and enterprise systems.
Experience applying AI/agentic technologies to transform business processes and deliver measurable outcomes.

Responsibilities

Establish a comprehensive framework for business and operational health beyond financial metrics.
Define critical KPIs, leading indicators, targets, ownership, and accountability.
Connect operational performance → business outcomes → financial impact.
Develop executive performance reviews focused on decisions, actions, and accountability.
Identify trends, systemic issues, and emerging risks before they impact results.
Build a comprehensive framework to measure NPI health, execution velocity, readiness, cost/margin, quality, risk, and post-launch performance.
Develop leading and predictive indicators to identify which programs are healthy, at risk, why, and what intervention is required.
Benchmark execution productivity and efficiency across products, programs, functions, resources and sites.
Move from descriptive reporting to diagnostic and predictive analytics.
Identify root causes and quantify the business and financial impact of operational issues and opportunities.
Integrate data across Finance, Engineering, Operations, Quality, Supply Chain, Product Management, and IT/Data.
Enable faster, fact-based resource, investment, and business decisions.
Assess the current state and define the target operating model, organization, and transformation roadmap.
Build a high-performing Business & Operational Analytics team with clear interfaces across Business, IT, and Data.
Simplify, standardize, automate, and transform processes using data, analytics, and AI.
Establish scalable tools, standards, and continuous-improvement mechanisms with clear accountability and measurable outcomes.
Partner with senior leaders to turn insights into decisions, actions, and business impact.
Identify and scale high-value opportunities for AI-enabled operational intelligence.
Develop predictive models for NPI risk, schedule, quality, supply, capacity, cost, and business outcomes.
Deploy AI agents and intelligent workflows to automate data gathering, analysis, issue identification, and performance management.
Move from static dashboards to intelligent, exception-based decision support.
Establish and scale an AI roadmap across PWR.
Initially focused on PCP, establish a scalable PWR Performance & Operational Intelligence capability.
Create common standards, metrics, systems, and operating mechanisms across PWR.
Provide leadership with an integrated view of NPI Health | Operational Performance | Productivity | Cost | Risk | Business Impact.